1. Field of the Invention
The present invention relates generally to geospatial data processing. More specifically, the present invention relates to precisely locating features on geospatial imagery.
2. Related Art
Geospatial imagery includes images of the Earth's surface taken from the air or from space. In combination with corresponding geospatial vector data, approximate locations of features on geospatial imagery can be determined. Such features may include buildings, roads, parcels, geological features, and so forth. Geospatial vector data can be any type of data that associates spatial attributes such as latitude and longitude coordinates to various sites on the Earth's surface. Geospatial vector data may also include non-spatial attributes like road names, house numbers, ZIP codes, ownership information, associated telephone numbers, tax information, valuation information, and so on.
Unfortunately, geospatial imagery and corresponding geospatial vector data are rarely mutually aligned. Misalignment between geospatial imagery and geospatial vector data can be caused by any number of variables. For example, geospatial imagery can be distorted due to the curvature of the Earth, the angle at which a given geospatial image was taken, minor movements in an imaging platform (e.g., a satellite or aircraft), and other errors associated with imaging techniques.
Due in part to the common misalignment between geospatial imagery and corresponding geospatial vector data, traditional approaches for locating features on geospatial imagery may not be accurate enough for commercial applications. Moreover, other approximations used in traditional approaches can further these inaccuracies. One existing approach for locating a specific address or property on geospatial imagery is to infer a location based on road vector data interpolation. Road vector data interpolation can be performed on a given road segment when the address number range as well as the latitude and longitude of the endpoints of that road segment are known. Using road vector data interpolation, a determined location of an address or property, relative to the actual location on the geospatial imagery, can have a substantial margin of error (e.g., 50 or more meters). Other similar existing approaches infer locations by interpolating between opposing corners of a given geospatial image, thus potentially resulting in even more drastic margins of error. A large margin of error in locating features on geospatial imagery can hinder usefulness in many various applications. As such, there is a need for improved techniques to precisely locate features on geospatial imagery using available geospatial data.